SBIR Phase II: Mobile Manipulation Hospital Service Robots

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project on hospital service robots is improving the quality of care in hospital systems that are under increased pressure to provide high-quality patient-centric care while functioning as profitable businesses. Hospitals face a shortage of qualified nurses and high rates of nurse turnover. Nurses play a critical role in communicating care plans, educating patients, and guarding against medical errors. The amount of time they spend in direct care activities is a key determinant of patient satisfaction, better patient outcomes, fewer errors, and shorter lengths of stay. In the face of nursing shortages across the U.S., it is increasingly important to have nurses performing at the 'top of their license'. Reducing the amount of time they spend on non-nursing tasks is crucial to this goal. Automation could address these challenges and labor shortage by allowing clinical staff to focus on providing skilled care. The proposed project aims to develop technology that is general-purpose enough to transfer to other markets, such as long term care facilities and, eventually, individual consumers. Robots that perform assistive tasks in homes could increase the feasibility of independent living for many older adults. The proposed project will establish the technical and commercial feasibility of developing hospital service robots that act as assistants on acute care units, enabling nurses to spend more time at the bedside with patients. This project will make technical advances along three dimensions: the ability of the proposed robot to autonomously navigate within nursing units and across the hospital (navigation capabilities); to easily adapt its manipulation skills to specific tasks and to physical characteristics of a particular hospital/unit (adaptive learning of manipulation skills); and to work alongside humans in a socially acceptable manner, including appropriate navigation in crowded hallways, speech, and eye gaze behaviors that communicate the robot's intentions (socially intelligent interoperability). The team intends to collaborate closely with a single partner hospital to iteratively improve the reliability and robustness of the artificial intelligence software suite developed with NSF funding and to deploy production-quality versions of the three core competencies. The final 6 months will involve a long-term deployment, with the robot autonomously working on an acute care unit of the partner hospital. The impact of the robot on unit staff and workflows will be documented, with the ultimate goal of developing a service robot that hospital staff view as a competent member of the care team.